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#### Eccentric binary black hole inspiral-merger-ringdown gravitational waveform model from numerical relativity and post-Newtonian theory

##### MPS-Authors
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Hinder,  Ian
Astrophysical and Cosmological Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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Pfeiffer,  Harald
Astrophysical and Cosmological Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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1709.02007.pdf
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##### Citation

Hinder, I., Kidder, L. E., & Pfeiffer, H. (2018). Eccentric binary black hole inspiral-merger-ringdown gravitational waveform model from numerical relativity and post-Newtonian theory. Physical Review D, 98: 044015. doi:10.1103/PhysRevD.98.044015.

Cite as: http://hdl.handle.net/21.11116/0000-0000-6390-D
##### Abstract
We present a prescription for computing gravitational waveforms for the inspiral, merger and ringdown of non-spinning eccentric binary black hole systems. The inspiral waveform is computed using the post-Newtonian expansion and the merger waveform is computed by interpolating a small number of quasi-circular NR waveforms. The use of circular merger waveforms is possible because eccentric binaries circularize in the last few cycles before the merger, which we demonstrate up to mass ratio $q = m_1/m_2 = 3$. The complete model is calibrated to 23 numerical relativity (NR) simulations starting ~20 cycles before the merger with eccentricities $e_\text{ref} \le 0.08$ and mass ratios $q \le 3$, where $e_\text{ref}$ is the eccentricity ~7 cycles before the merger. The NR waveforms are long enough that they start above 30 Hz (10 Hz) for BBH systems with total mass $M \ge 80 M_\odot$ ($230 M_\odot$). We find that, for the sensitivity of advanced LIGO at the time of its first observing run, the eccentric model has a faithfulness with NR of over 97% for systems with total mass $M \ge 85 M_\odot$ across the parameter space ($e_\text{ref} \le 0.08, q \le 3$). For systems with total mass $M \ge 70 M_\odot$, the faithfulness is over 97% for $e_\text{ref} \lesssim 0.05$ and $q \le 3$. The NR waveforms and the Mathematica code for the model are publicly available.